| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_b051f9f7933c758e66f6ceda5c9fb2cc |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-044
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B2219-2639
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C01B2210-0045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-01 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C01B21-0405
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-0283
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B13-0265
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C01C1-0482
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-0235
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C25B15-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C25B1-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2148
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-0229 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/C25B1-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/C25B15-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/C01B21-04 |
| filingDate |
2022-03-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f4e8973e58d95999bd409748432b0fab
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_56f7a4df3ba24fac39ab3f6e59eb4a4e |
| publicationDate |
2022-09-09-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-115034398-A |
| titleOfInvention |
Method and apparatus for monitoring operational characteristics of industrial gas equipment complexes |
| abstract |
A method of monitoring operational characteristics of an industrial gas plant complex including a plurality of industrial gas plants is provided. The method is performed by at least one hardware processor and includes: assigning a machine learning model to each of the industrial gas plants forming the industrial gas plant complex; performing time-dependent operations based on the received historical time of the respective industrial gas plant characteristic data to train a corresponding machine learning model for each industrial gas equipment; perform the trained machine learning model on each industrial gas equipment to predict the operational characteristics of each corresponding industrial gas equipment for a predetermined future time period; and The predicted operating characteristic data for each respective industrial gas plant for a predetermined future time period is compared to the measured operating characteristic data for the corresponding time period to identify deviations in industrial gas plant performance. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115732041-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115732041-B |
| priorityDate |
2021-03-05-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |